Optimizing Nitrogen Oxide Emissions in Industrial Calcination through Staged Combustion: A CFD-, MP-PIC-, and RSM-Based Approach for Enhanced Process Efficiency

This study develops a comprehensive numerical model employing computational fluid dynamics for the precise prediction of nitrogen oxide (NO) formation and reduction in industrial-scale calciners. Through the integration of Euler–Lagrange and multiphase particle in cell methods with a global chemical kinetic reaction model, it explores the complex dynamics of NO migration and mitigation strategies. The research validates the model against empirical data from a cement plant, revealing the limited impact of traditional staged combustion due to the reduction zone’s size constraints. By extending the calciner structure and optimizing operational parameters such as the coal feed ratio and the O2 concentration, identified through response surface analysis, the study successfully reduces NO concentrations to approximately 310 ppm. These findings contribute significantly to the field of environmental engineering by offering a validated approach for improving low-nitrogen combustion in cement manufacturing. The advancements demonstrated in this research provide a solid foundation for further innovation in combustion technology, aiming at more efficient and environmentally sustainable industrial applications.

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Publication Details

Journal
Industrial & Engineering Chemistry Research
Published
2024-08-09
DOI
https://doi.org/10.1021/acs.iecr.4c01329
Citations
2
Primary Topic
Thermochemical Biomass Conversion Processes
Type
article
Field-Weighted Citation Impact
0.37
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article

Optimizing Nitrogen Oxide Emissions in Industrial Calcination through Staged Combustion: A CFD-, MP-PIC-, and RSM-Based Approach for Enhanced Process Efficiency

Tengfei Yin, Pei Shui, G Wang, Yujie Tian et al.
2 citations
Industrial & Engineering Chemistry Research
Thermochemical Biomass Conversion Processes
0.37
article

Optimizing Nitrogen Oxide Emissions in Industrial Calcination through Staged Combustion: A CFD-, MP-PIC-, and RSM-Based Approach for Enhanced Process Efficiency

Tengfei Yin, Pei Shui, G Wang, Yujie Tian, Hongkun Cui
article en
2 citations

Abstract

This study develops a comprehensive numerical model employing computational fluid dynamics for the precise prediction of nitrogen oxide (NO) formation and reduction in industrial-scale calciners. Through the integration of Euler–Lagrange and multiphase particle in cell methods with a global chemical kinetic reaction model, it explores the complex dynamics of NO migration and mitigation strategies. The research validates the model against empirical data from a cement plant, revealing the limited impact of traditional staged combustion due to the reduction zone’s size constraints. By extending the calciner structure and optimizing operational parameters such as the coal feed ratio and the O2 concentration, identified through response surface analysis, the study successfully reduces NO concentrations to approximately 310 ppm. These findings contribute significantly to the field of environmental engineering by offering a validated approach for improving low-nitrogen combustion in cement manufacturing. The advancements demonstrated in this research provide a solid foundation for further innovation in combustion technology, aiming at more efficient and environmentally sustainable industrial applications.

Industrial & Engineering Chemistry ResearchVol. 63(33)
Hefei Cement Research Design Institute (CN), Institute of Process Engineering (CN)
Affordable and clean energy
Openalex Percentile: Top 44%
Thermochemical Biomass Conversion Processes
0.37
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Optimizing Nitrogen Oxide Emissions in Industrial Calcination through Staged Combustion: A CFD-, MP-PIC-, and RSM-Based Approach for Enhanced Process Efficiency — Tengfei Yin, Pei Shui, et al. · Industrial & Engineering Chemistry Research (2024) | TGRS Research Map | TGRS